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Word sense disambiguation: a survey
- ACM COMPUTING SURVEYS
, 2009
"... Word sense disambiguation (WSD) is the ability to identify the meaning of words in context in a computational manner. WSD is considered an AI-complete problem, that is, a task whose solution is at least as hard as the most difficult problems in artificial intelligence. We introduce the reader to the ..."
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Cited by 191 (16 self)
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Word sense disambiguation (WSD) is the ability to identify the meaning of words in context in a computational manner. WSD is considered an AI-complete problem, that is, a task whose solution is at least as hard as the most difficult problems in artificial intelligence. We introduce the reader to the motivations for solving the ambiguity of words and provide a description of the task. We overview supervised, unsupervised, and knowledge-based approaches. The assessment of WSD systems is discussed in the context of the Senseval/Semeval campaigns, aiming at the objective evaluation of systems participating in several different disambiguation tasks. Finally, applications, open problems, and future directions are discussed.
Abstract Tags are not Metadata, but “Just More Content” – to Some People ∗
"... The authoring of tags – unlike the authoring of traditional metadata – is highly popular among users. This harbours unprecedented opportunities for organizing content. However, tags are still poorly understood. What do they “mean”, in what senses are they similar to or different from metadata? Diffe ..."
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Cited by 14 (0 self)
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The authoring of tags – unlike the authoring of traditional metadata – is highly popular among users. This harbours unprecedented opportunities for organizing content. However, tags are still poorly understood. What do they “mean”, in what senses are they similar to or different from metadata? Different tags support different communities, but how exactly do they reflect the plurality of opinions,what is the relation to individual differences in authoring and reading? In this paper, we offer a definition and empirical evidence for the claim that “tags are not metadata, but just more content”. The analysis rests on a multi-annotator classification of a blog corpus using the WordNet domain labels system (WND), the development of a system of text-classification methods using WordNet and WND, and a quantitative and qualitative comparative analysis of these classifications. We argue that the notion of a “gold standard ” may be meaningless in social media, and we outline possible consequences for labelling and search-engine development.
Understanding weblog communities through digital traces: A framework, a tool and an example
- Proc. of the OTM 2006 Workshops, LNCS 4277
, 2006
"... Abstract. Often research on online communities could be compared to archaeology [16]: researchers look at patterns in digital traces that members leave to characterise the community they belong to. Relatively easy access to these traces and a growing number of methods and tools to collect and analys ..."
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Cited by 4 (1 self)
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Abstract. Often research on online communities could be compared to archaeology [16]: researchers look at patterns in digital traces that members leave to characterise the community they belong to. Relatively easy access to these traces and a growing number of methods and tools to collect and analyse them make such analysis increasingly attractive. However, a researcher is faced with the difficult task of choosing which digital artefacts and which relations between them should be taken into account, and how the findings should be interpreted to say something meaningful about the community based on the traces of its members. In this paper we present a framework that allows categorising digital traces of an online community along five dimensions (people, documents, terms, links and time) and then describe a tool that supports the analysis of community traces by combining several of them, illustrating the types of analysis possible using a dataset from a weblog community. 1
Design of a Recommendation Model Considering Semantic Analysis
"... The Social networking site is increasingly used as a channel for reaching end users. Personalized Recommender system can work on participatory media content and enhance CMC (computer mediated communication) ultimately providing the user with the finest items of interest. It collects data implicitly ..."
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The Social networking site is increasingly used as a channel for reaching end users. Personalized Recommender system can work on participatory media content and enhance CMC (computer mediated communication) ultimately providing the user with the finest items of interest. It collects data implicitly as well as explicitly and takes into consideration user activity, preferences, and ratings to evaluate weights for calculation of trust, social intimacy, popularity and semantic scores. The accumulation of these scores generates the final recommendation score and based on it a recommendation list is generated for each user.Several important theories in this regard have proven to be viable and some not so feasible. Thus comparative study of some recommendation systems can throw light on the problems faced and suggest solutions in this regard.
An Analysis of Personal Medical Information Disclosed in YouTube Videos Created by Patients with Multiple Sclerosis
"... Abstract. The Internet has become one of the main sources of health information. Today, content generation is no longer limited to the healthcare professionals of the late nineties; Web 2.0 services and platforms have empowered patients to create and interact with various forms of Patient-Generated ..."
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Abstract. The Internet has become one of the main sources of health information. Today, content generation is no longer limited to the healthcare professionals of the late nineties; Web 2.0 services and platforms have empowered patients to create and interact with various forms of Patient-Generated Content (PGC); these include: videos, blogs, and social networking pages, among others. This investigation evaluated the characteristics of PGC found within YouTube video comments. We selected a random sample of 25 out of 769 Multiple Sclerosis patient-generated videos and analyzed their corresponding 557 comments for health information. 320 comments met the inclusion criteria and 70 contained personal health information (PHI). Comments with PHI were sub-characterized for the type of medical information (i.e., diagnosis, date of diagnosis, medication, among others). In this descriptive study, we present the strata within this content and postulate some of the corresponding patient risks and ethical challenges associated with PGC found in YouTube video comments.
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"... The thesis may be consulted by you, provided you comply with the provisions of the Act and the following conditions of use: Any use you make of these documents or images must be for research or private study purposes only, and you may not make them available to any other person. Authors control th ..."
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The thesis may be consulted by you, provided you comply with the provisions of the Act and the following conditions of use: Any use you make of these documents or images must be for research or private study purposes only, and you may not make them available to any other person. Authors control the copyright of their thesis. You will recognise the author’s right to be identified as the author of the thesis, and due acknowledgement will be made to the author where appropriate. You will obtain the author’s permission before publishing any material from the thesis. 1
